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dti = pd.date_range('2016-01-01', periods=3) nat = np.timedelta64('NaT') dta = dti._data.copy() dta[0] = nat # <-- should raise TypeError, doesn't ser = pd.Series(dti.copy()) ser[1] = nat # <-- should raise TypeError, doesn't df = pd.DataFrame(dti.copy()) df.loc[2, 0] = nat # <-- should raise TypeError, doesn't
I haven't checked, but I expect the same thing happens in reverse for Timedelta, possible Period dtypes.
The text was updated successfully, but these errors were encountered:
"should" behavior in OP is wrong, it should cast to object dtype, but does does not
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BUG: Fix inserting of wrong-dtyped NaT, closes #27297 (#27311)
76247c1
I think I incorrectly marked #27311 as closing this, while that only fixes the Series portion of this. I still need to fix the DTA version.
Woops, #27331 does fix the other half of this.
BUG: Fix inserting of wrong-dtyped NaT, closes pandas-dev#27297 (pand…
17a5d49
…as-dev#27311)
Successfully merging a pull request may close this issue.
I haven't checked, but I expect the same thing happens in reverse for Timedelta, possible Period dtypes.
The text was updated successfully, but these errors were encountered: